All references cited anywhere in this specification are incorporated herein by reference.
Cone-beam CT (CBCT) is finding increased application in areas such as image-guided surgery (IGS), image-guided radiation therapy (IGRT), and interventional radiology. In many of these applications, repeat CBCT scans are often acquired. For example, in IGS, an initial CBCT may be used for patient setup and registration of preoperative planning information, while subsequent CBCTs may be used for visualizing surgical progress, detection of complications, and/or verifying the surgical product. Additionally, in IGRT, patients may receive a CBCT scan at each treatment fraction. In accordance with efforts to reduce radiation dose to the patient (and in some cases to the clinicians, as with IGS), each CBCT should be acquired at the minimum dose such that a particular imaging task(s) can still be reliably performed. For scenarios in which multiple CBCTs of a patient are acquired, ensuring that each scan is conducted at the minimum dose sufficient for a given imaging task is especially important in reducing the total accumulated dose, since a fractional dose reduction per scan is multiplicative with the number of scans. Of course, lower dose techniques generally produce higher noise images, and selection of the minimum-dose protocol for a particular patient is challenging—usually guided simply by a coarse technique chart in which scan protocols are simply stratified by patient body habitus. The ability to confidently select low-dose protocols sufficient for a given imaging task and patient is therefore a challenge, and perhaps even more so for nonlinear model-based image reconstruction (MBIR) methods for which complex dose-noise-resolution tradeoffs may defy a simple predictive model.
Typically, a method utilized to aid in selecting a patient- and task-specific protocol (i.e., acquisition technique, image reconstruction method, and image processing/post-processing parameters) is to provide a “low-dose preview” (LDP) of the image quality that can be expected for a CBCT image acquired at reduced dose. This allows the user to visualize image quality at a particular reduced dose and confidently select a minimum-dose protocol sufficient for the imaging task.
More recently, simulated dose reduction methods have utilized models of noise beyond just quantum noise, such as the inclusion of electronic noise, which led to accurate reproduction of not only image noise magnitude but also noise power spectra. Other extensions of simulated dose reduction include using dual energy scans to allow simulated changes in tube voltage or using an image-based approach that does not assume availability of projection data (but does not allow for different reconstruction methods/parameters). Common to these methods is the assumption of spatially uncorrelated noise in the projection data, which may be a fair assumption for detectors employed in multi-detector CT scanners.
However, correlated noise is an important consideration for flat-panel detectors (FPDs) that are typically used in CBCT—for example, scintillator blur is known to introduce spatial correlation in the quantum noise, and electronic noise can be an important source of noise at very low dose levels. Therefore, previous methods for low-dose simulation in CT cannot be directly extended to CBCT based on indirect-detection FPDs since they do not include the effect of correlated noise (quantum or electronic noise).